While we frequently on SBM target the worst abuses of science in medicine, it’s important to recognize that doing rigorous science is complex and mainstream scientists often fall short of the ideal. In fact, one of the advantages of exploring pseudoscience in medicine is developing a sensitive detector for errors in logic, method, and analysis. Many of the errors we point out in so-called “alternative” medicine also crop up elsewhere in medicine – although usually to a much less degree.
It is not uncommon, for example, for a paper to fail to adjust for multiple analysis – if you compare many variables you have to take that into consideration when doing the statistical analysis otherwise the probability of a chance correlation will be increased.
I discussed just yesterday on NeuroLogica the misapplication of meta-analysis – in this case to the question of whether or not CCSVI correlates with multiple sclerosis. I find this very common in the literature, essentially a failure to appreciate the limits of this particular analysis tool.
Another example comes recently from the journal Nature Neuroscience (an article I learned about from Ben Goldacre over at the Bad Science blog). Erroneous analyses of interactions in neuroscience: a problem of significance investigates the frequency of a subtle but important statistical error in high profile neuroscience journals.